Data integration for heterogeneous data: A general framework for distribution shift, posterior drift and block missing data

In the era of big data, researchers and analysts have unprecedented access to extensive datasets, opening up new opportunities for scientific discovery and predictive modeling. These datasets, often collected from different sources, contain various forms of heterogeneity, such as distribution heterogeneity, observation heterogeneity, and task…